Gastric Section Correlation Network for Gastric Precancerous Lesion Diagnosis.

Goal: Diagnosing the corpus-predominant gastritis index (CGI) which is an early precancerous lesion in the stomach has been shown its effectiveness in identifying high gastric cancer risk patients for preventive healthcare. However, invasive biopsies and time-consuming pathological analysis are required for the CGI diagnosis. Methods: We propose a novel gastric section correlation network (GSCNet) for the CGI diagnosis from endoscopic images of three dominant gastric sections, the antrum, body and cardia. The proposed network consists of two dominant modules including the scaling feature fusion module and section correlation module. The front one aims to extract scaling fusion features which can effectively represent the mucosa under variant viewing angles and scale changes for each gastric section. The latter one aims to apply the medical prior knowledge with three section correlation losses to model the correlations of different gastric sections for the CGI diagnosis. Results: The proposed method outperforms competing deep learning methods and achieves high testing accuracy, sensitivity, and specificity of 0.957, 0.938 and 0.962, respectively. Conclusions: The proposed method is the first method to identify high gastric cancer risk patients with CGI from endoscopic images without invasive biopsies and time-consuming pathological analysis.

Video Summarization With Spatiotemporal Vision Transformer.

Video summarization aims to generate a compact summary of the original video for efficient video browsing. To provide video summaries which are consistent with the human perception and contain important content, supervised learning-based video summarization methods are proposed. These methods aim to learn important content based on continuous frame information of human-created summaries. However, simultaneously considering both of inter-frame correlations among non-adjacent frames and intra-frame attention which attracts the humans for frame importance representations are rarely discussed in recent methods. To address these issues, we propose a novel transformer-based method named spatiotemporal vision transformer (STVT) for video summarization. The STVT is composed of three dominant components including the embedded sequence module, temporal inter-frame attention (TIA) encoder, and spatial intra-frame attention (SIA) encoder. The embedded sequence module generates the embedded sequence by fusing the frame embedding, index embedding and segment class embedding to represent the frames. The temporal inter-frame correlations among non-adjacent frames are learned by the TIA encoder with the multi-head self-attention scheme. Then, the spatial intra-frame attention of each frame is learned by the SIA encoder. Finally, a multi-frame loss is computed to drive the learning of the network in an end-to-end trainable manner. By simultaneously using both inter-frame and intra-frame information, our method outperforms state-of-the-art methods in both of the SumMe and TVSum datasets. The source code of the spatiotemporal vision transformer will be available at https://github.com/nchucvml/STVT.

Comparison Between Bicuspid and Tricuspid Aortic Regurgitation: Presentation, Survival, and Aorta Complications.

Background: Although the Asian population is growing globally, data in Asian subjects regarding differences between bicuspid aortic valve (BAV) and tricuspid aortic valve (TAV) in aortic regurgitation (AR) remain unexplored. Objectives: The aim of this study was to examine differences between Asian BAV-AR and TAV-AR in significant AR, including aorta complications. Methods: The study included 711 consecutive patients with chronic moderate to severe and severe AR from 2008 to 2020. Outcomes included all-cause death, aortic valve surgery (AVS), and incidence of aortic dissection (AD). Results: There were 149 BAV-AR (mean age: 48 ± 16 years) and 562 TAV-AR (mean age: 68 ± 15 years; P < 0.0001) patients; baseline indexed left ventricle and indexed aorta size were larger in TAV-AR. Total follow-up was 4.8 years (IQR: 2.0-8.4 years), 252 underwent AVS, and 185 died during follow-up; 18 cases (only 1 BAV) of AD occurred, with a mean maximal aorta size of 60 ± 9 mm. The 10-year AVS incidence was higher in TAV-AR (51% ± 4%) vs BAV-AR (40% ± 5%) even after adjustment for covariates (P < 0.0001). The 10-year survival was higher in BAV-AR (86% ± 4%) vs TAV-AR (57% ± 3%; P < 0.0001) and became insignificant after age adjustment (P = 0.33). Post-AVS 10-year survival was 93% ± 5% in BAV-AR and 78% ± 5% in TAV-AR, respectively (P = 0.08). The 10-year incidence of AD was higher in TAV-AR (4.8% ± 1.5%) than in BAV-AR (0.9% ± 0.9%) and was determined by aorta size ≥45 mm (P ≤ 0.015). Compared with an age- and sex-matched population in Taiwan, TAV-AR (HR: 3.1) had reduced survival (P < 0.0001). Conclusions: Our findings suggest that TAV-AR patients were at a later stage of AR course and had a high AD rate as opposed to BAV-AR patients in Taiwan, emphasizing the importance of early referral for timely management. Surgery on the aorta with a lower threshold in TAV-AR should be considered.

Dynamic changes in heparin-binding protein as a prognostic biomarker for 30-day mortality in sepsis patients in the intensive care unit.

Heparin-binding protein (HBP) has been shown to be a robust predictor of the progression to organ dysfunction from sepsis, and we hypothesized that dynamic changes in HBP may reflect the severity of sepsis. We therefore aim to investigate the predictive value of baseline HBP, 24-h, and 48-h HBP change for prediction of 30-day mortality in adult patients with sepsis. This is a prospective observational study in an intensive care unit of a tertiary center. Patients aged 20 years or older who met SEPSIS-3 criteria were prospectively enrolled from August 2019 to January 2020. Plasma levels of HBP were measured at admission, 24 h, and 48 h and dynamic changes in HBP were calculated. The Primary endpoint was 30-day mortality. We tested whether the biomarkers could enhance the predictive accuracy of a multivariable predictive model. A total of 206 patients were included in the final analysis. 48-h HBP change (HBPc-48 h) had greater predictive accuracy of area under the curve (AUC: 0.82), followed by baseline HBP (0.79), PCT (0.72), lactate (0.71), and CRP (0.65), and HBPc-24 h (0.62). Incorporation of HBPc-48 h into a clinical prediction model significantly improved the AUC from 0.85 to 0.93. HBPc-48 h may assist clinicians with clinical outcome prediction in critically ill patients with sepsis and can improve the performance of a prediction model including age, SOFA score and Charlson comorbidity index.

Predicting Sepsis Mortality in a Population-Based National Database: Machine Learning Approach.

BACKGROUND: Although machine learning (ML) algorithms have been applied to point-of-care sepsis prognostication, ML has not been used to predict sepsis mortality in an administrative database. Therefore, we examined the performance of common ML algorithms in predicting sepsis mortality in adult patients with sepsis and compared it with that of the conventional context knowledge-based logistic regression approach. OBJECTIVE: The aim of this study is to examine the performance of common ML algorithms in predicting sepsis mortality in adult patients with sepsis and compare it with that of the conventional context knowledge-based logistic regression approach. METHODS: We examined inpatient admissions for sepsis in the US National Inpatient Sample using hospitalizations in 2010-2013 as the training data set. We developed four ML models to predict in-hospital mortality: logistic regression with least absolute shrinkage and selection operator regularization, random forest, gradient-boosted decision tree, and deep neural network. To estimate their performance, we compared our models with the Super Learner model. Using hospitalizations in 2014 as the testing data set, we examined the models' area under the receiver operating characteristic curve (AUC), confusion matrix results, and net reclassification improvement. RESULTS: Hospitalizations of 923,759 adults were included in the analysis. Compared with the reference logistic regression (AUC: 0.786, 95% CI 0.783-0.788), all ML models showed superior discriminative ability (P<.001), including logistic regression with least absolute shrinkage and selection operator regularization (AUC: 0.878, 95% CI 0.876-0.879), random forest (AUC: 0.878, 95% CI 0.877-0.880), xgboost (AUC: 0.888, 95% CI 0.886-0.889), and neural network (AUC: 0.893, 95% CI 0.891-0.895). All 4 ML models showed higher sensitivity, specificity, positive predictive value, and negative predictive value compared with the reference logistic regression model (P<.001). We obtained similar results from the Super Learner model (AUC: 0.883, 95% CI 0.881-0.885). CONCLUSIONS: ML approaches can improve sensitivity, specificity, positive predictive value, negative predictive value, discrimination, and calibration in predicting in-hospital mortality in patients hospitalized with sepsis in the United States. These models need further validation and could be applied to develop more accurate models to compare risk-standardized mortality rates across hospitals and geographic regions, paving the way for research and policy initiatives studying disparities in sepsis care.

Genome-wide association study of primary dysmenorrhea in the Taiwan Biobank validates associations near the NGF and IL1 gene loci.

Using the Taiwan Biobank, we aimed to identify traits and genetic variations that could predispose Han Chinese women to primary dysmenorrhea. Cases of primary dysmenorrhea included those who self-reported "frequent dysmenorrhea" in a dysmenorrhea-related Taiwan Biobank questionnaire, and those who have been diagnosed with severe dysmenorrhea by a physician. Controls were those without self-reported dysmenorrhea. Customized Axiom-Taiwan Biobank Array Plates were used to perform whole-genome genotyping, PLINK was used to perform association tests, and HaploReg was used to conduct functional annotations of SNPs and bioinformatic analyses. The GWAS analysis included 1186 cases and 24,020 controls. We identified 53 SNPs that achieved genome-wide significance (P < 5 × 10-8, which clustered in 2 regions. The first SNP cluster was on chromosome 1, and included 24 high LD (R2 > 0.88) variants around the NGF gene (lowest P value of 3.83 × 10-13 for rs2982742). Most SNPs occurred within NGF introns, and were predicted to alter regulatory binding motifs. The second SNP cluster was on chromosome 2, including 7 high LD (R2 > 0.94) variants around the IL1A and IL1B loci (lowest P value of 7.43 × 10-10 for rs11676014) and 22 SNPs that did not reach significance after conditional analysis. Most of these SNPs resided within IL1A and IL1B introns, while 2 SNPs may be in the promoter histone marks or promoter flanking regions of IL1B. To conclude, data from this study suggest that NGF, IL1A, and IL1B may be involved in the pathogenesis of primary dysmenorrhea in the Han Chinese in Taiwan.

Association Between Aspirin Use and Sepsis Outcomes: A National Cohort Study.

BACKGROUND: Aspirin has anti-inflammatory and antiplatelet activities and directly inhibits bacterial growth. These effects of aspirin may improve survival in patients with sepsis. We retrospectively reviewed a large national health database to test the relationship between prehospital aspirin use and sepsis outcomes. METHODS: We conducted a retrospective population-based cohort study using the National Health Insurance Research Database of Taiwan from 2001 to 2011 to examine the relationship between aspirin use before hospital admission and sepsis outcomes. The association between aspirin use and 90-day mortality in sepsis patients was determined using logistic regression models and weighting patients by the inverse probability of treatment weighting (IPTW) with the propensity score. Kaplan-Meier survival curves for each IPTW cohort were plotted for 90-day mortality. For sensitivity analyses, restricted mean survival times (RMSTs) were calculated based on Kaplan-Meier curves with 3-way IPTW analysis comparing current use, past use, and nonuse. RESULTS: Of 52,982 patients with sepsis, 12,776 took aspirin before hospital admission (users), while 39,081 did not take any antiplatelet agents including aspirin before hospital admission (nonusers). After IPTW analysis, we found that when compared to nonusers, patients who were taking aspirin within 90 days before sepsis onset had a lower 90-day mortality rate (IPTW odds ratio [OR], 0.90; 95% confidence interval [CI], 0.88-0.93; P < .0001). Based on IPTW RMST analysis, nonusers had an average survival of 71.75 days, while current aspirin users had an average survival of 73.12 days. The difference in mean survival time was 1.37 days (95% CI, 0.50-2.24; P = .002). CONCLUSIONS: Aspirin therapy before hospital admission is associated with a reduced 90-day mortality in sepsis patients.

In-hospital Cardiac Arrest in Patients With Sepsis: A National Cohort Study.

Background: Little is known about the risk of in-hospital cardiac arrest (IHCA) among patients with sepsis. We aimed to characterize the incidence and outcome of IHCA among patients with sepsis in a national database. We then determined the major risk factors associated with IHCA among sepsis patients. Methods: We used data from a population-based cohort study based on the National Health Insurance Research Database of Taiwan (NHRID) between 2000 and 2013. We used Martin's implementation that combined the explicit ICD-9 CM codes for sepsis and six major organ dysfunction categories. IHCA among sepsis patients was identified by the presence of cardiopulmonary resuscitation procedures. The survival impact was analyzed with the Cox proportional-hazards model using inverse probability of treatment weighting (IPTW). The risk factors were identified by logistic regression models with 10-fold cross-validation, adjusting for competing risks. Results: We identified a total of 20,022 patients with sepsis, among whom 2,168 developed in-hospital cardiac arrest. Sepsis patients with a higher burden of comorbidities and organ dysfunction were more likely to develop in-hospital cardiac arrest. Acute respiratory failure, hematological dysfunction, renal dysfunction, and hepatic dysfunction were associated with increased risk of IHCA. Regarding the source of infection, patients with respiratory tract infections were at the highest risk, whereas patients with urinary tract infections and primary bacteremia were less likely to develop IHCA. The risk of IHCA correlated well with age and revised cardiac risk index (RCRI). The final competing risk model concluded that acute respiratory failure, male gender, and diabetes are the three strongest predictors for IHCA. The effect of IHCA on survival can last 1 year after hospital discharge, with an IPTW-weighted hazard ratio of 5.19 (95% CI: 5.06, 5.35) compared to patients who did not develop IHCA. Conclusion: IHCA in sepsis patients had a negative effect on both short- and long-term survival. The risk of IHCA among hospitalized sepsis patients was strongly correlated with age and cardiac risk index. The three identified risk factors can help clinicians to identify patients at higher risk for IHCA.

Validation of a Post-Transplant Lymphoproliferative Disorder Risk Prediction Score and Derivation of a New Prediction Score Using a National Bone Marrow Transplant Registry Database.

BACKGROUND: We externally validated Fujimoto's post-transplant lymphoproliferative disorder (PTLD) scoring system for risk prediction by using the Taiwan Blood and Marrow Transplant Registry Database (TBMTRD) and aimed to create a superior scoring system using machine learning methods. MATERIALS AND METHODS: Consecutive allogeneic hematopoietic cell transplant (HCT) recipients registered in the TBMTRD from 2009 to 2018 were included in this study. The Fujimoto PTLD score was calculated for each patient. The machine learning algorithm, least absolute shrinkage and selection operator (LASSO), was used to construct a new score system, which was validated using the fivefold cross-validation method. RESULTS: We identified 2,148 allogeneic HCT recipients, of which 57 (2.65%) developed PTLD in the TBMTRD. In this population, the probabilities for PTLD development by Fujimoto score at 5 years for patients in the low-, intermediate-, high-, and very-high-risk groups were 1.15%, 3.06%, 4.09%, and 8.97%, respectively. The score model had acceptable discrimination with a C-statistic of 0.65 and a near-perfect moderate calibration curve (HL test p = .81). Using LASSO regression analysis, a four-risk group model was constructed, and the new model showed better discrimination in the validation cohort when compared with The Fujimoto PTLD score (C-statistic: 0.75 vs. 0.65). CONCLUSION: Our study demonstrated a more comprehensive model when compared with Fujimoto's PTLD scoring system, which included additional predictors identified through machine learning that may have enhanced discrimination. The widespread use of this promising tool for risk stratification of patients receiving HCT allows identification of high-risk patients that may benefit from preemptive treatment for PTLD. IMPLICATIONS FOR PRACTICE: This study validated the Fujimoto score for the prediction of post-transplant lymphoproliferative disorder (PTLD) development following hematopoietic cell transplant (HCT) in an external, independent, and nationally representative population. This study also developed a more comprehensive model with enhanced discrimination for better risk stratification of patients receiving HCT, potentially changing clinical managements in certain risk groups. Previously unreported risk factors associated with the development of PTLD after HCT were identified using the machine learning algorithm, least absolute shrinkage and selection operator, including pre-HCT medical history of mechanical ventilation and the chemotherapy agents used in conditioning regimen.

Risk of out-of-hospital cardiac arrest among sepsis survivors in Taiwan: analysis of a nationwide population-based cohort.

OBJECTIVES: There is minimal literature examining the association of sepsis with out-of-hospital cardiac arrest (OHCA). Using a large national database, we aimed to quantify the risk of OHCA among sepsis patients after hospital discharge. DESIGN: Population-based cohort study. SETTING: Nationwide sepsis cohort retrieved from the National Health Insurance Research Database of Taiwan between 2000 and 2013. PARTICIPANTS: We included 17 304 patients with sepsis. After hospital discharge, 144 patients developed OHCA within 30 days and 640 between days 31 and 365. PRIMARY AND SECONDARY OUTCOME MEASURES: The main outcomes were OHCA events following hospital discharge for sepsis. To evaluate the independent association between sepsis and OHCA after a sepsis hospitalisation, we constructed two non-sepsis comparison cohorts using risk set sampling and propensity score matching techniques (non-infection cohort, non-sepsis infection cohort). We plotted the daily number and daily risk of OHCA within 1 year of hospital discharge between sepsis and matched non-sepsis cohorts. We used Cox regression to evaluate the risk of early and late OHCA, comparing sepsis to non-sepsis patients. RESULTS: Compared with non-infected patients, sepsis patients had a higher rate of early (HR 1.66, 95% CI: 1.27 to 2.16) and late (HR 1.19, 95% CI: 1.06 to 1.33) OHCA events. This association was independent of age, sex or cardiovascular history. Compared with non-sepsis patients with infections, sepsis patients had a higher rate of both early (HR 1.28, 95% CI: 1.00 to 1.63) and late (HR 1.13, 95% CI: 1.01 to 1.27) OHCA events, especially among patients with cardiovascular disease (OR 1.35, 95% CI: 1.01 to 1.81). CONCLUSIONS: Sepsis patients had increased risk of OHCA compared with matched non-sepsis controls, which lasted up to 1 year after hospital discharge.

Temporal Trends in Sepsis Incidence and Mortality in Patients With Cancer in the US Population.

BACKGROUND: Few population-based studies assess the impact of cancer on sepsis incidence and mortality. OBJECTIVES: To evaluate epidemiological trends of sepsis in patients with cancer. METHODS: This retrospective cohort study included adults (≥20 years old) identified using sepsis-indicator International Classification of Diseases codes from the Nationwide Inpatient Sample database (2006-2014). A generalized linear model was used to trend incidence and mortality. Outcomes in patients with cancer and patients without cancer were compared using propensity score matching. Cox regression modeling was used to calculate hazard ratios for mortality rates. RESULTS: The study included 13 996 374 patients, 13.6% of whom had cancer. Gram-positive infections were most common, but the incidence of gram-negative infections increased at a greater rate. Compared with patients without cancer, those with cancer had significantly higher rates of lower respiratory tract (35.0% vs 31.6%), intra-abdominal (5.5% vs 4.6%), fungal (4.8% vs 2.9%), and anaerobic (1.2% vs 0.9%) infections. Sepsis incidence increased at a higher rate in patients with cancer than in those without cancer, but hospital mortality rates improved equally in both groups. After propensity score matching, hospital mortality was higher in patients with cancer than in those without cancer (hazard ratio, 1.25; 95% CI, 1.24-1.26). Of patients with sepsis and cancer, those with lung cancer had the lowest survival (hazard ratio, 1.65) compared with those with breast cancer, who had the highest survival. CONCLUSIONS: Cancer patients are at high risk for sepsis and associated mortality. Research is needed to guide sepsis monitoring and prevention in patients with cancer.

Neuroprognostic Accuracy of Quantitative Versus Standard Pupillary Light Reflex for Adult Postcardiac Arrest Patients: A Systematic Review and Meta-Analysis.

OBJECTIVES: An automated infrared pupillometer measures quantitative pupillary light reflex using a calibrated light stimulus. We examined whether the timing of performing quantitative pupillary light reflex or standard pupillary light reflex may impact its neuroprognostic performance in postcardiac arrest comatose patients and whether quantitative pupillary light reflex may outperform standard pupillary light reflex in early postresuscitation phase. DATA SOURCES: PubMed and Embase databases from their inception to July 2020. STUDY SELECTION: We selected studies providing sufficient data of prognostic values of standard pupillary light reflex or quantitative pupillary light reflex to predict neurologic outcomes in adult postcardiac arrest comatose patients. DATA EXTRACTION: Quantitative data required for building a 2 × 2 contingency table were extracted, and study quality was assessed using standard criteria. DATA SYNTHESIS: We used the bivariate random-effects model to estimate the pooled sensitivity and specificity of standard pupillary light reflex or quantitative pupillary light reflex in predicting poor neurologic outcome during early (< 72 hr), middle (between 72 and 144 hr), and late (≧ 145 hr) postresuscitation periods, respectively. We included 39 studies involving 17,179 patients. For quantitative pupillary light reflex, the cut off points used in included studies to define absent pupillary light reflex ranged from 0% to 13% (median: 7%) and from zero to 2 (median: 2) for pupillary light reflex amplitude and Neurologic Pupil index, respectively. Late standard pupillary light reflex had the highest area under the receiver operating characteristic curve (0.98, 95% CI [CI], 0.97-0.99). For early standard pupillary light reflex, the area under the receiver operating characteristic curve was 0.80 (95% CI, 0.76-0.83), with a specificity of 0.91 (95% CI, 0.85-0.95). For early quantitative pupillary light reflex, the area under the receiver operating characteristic curve was 0.83 (95% CI, 0.79-0.86), with a specificity of 0.99 (95% CI, 0.91-1.00). CONCLUSIONS: Timing of pupillary light reflex examination may impact neuroprognostic accuracy. The highest prognostic performance was achieved with late standard pupillary light reflex. Early quantitative pupillary light reflex had a similar specificity to late standard pupillary light reflex and had better specificity than early standard pupillary light reflex. For postresuscitation comatose patients, early quantitative pupillary light reflex may substitute for early standard pupillary light reflex in the neurologic prognostication algorithm.

Comparing mortality between positive and negative blood culture results: an inverse probability of treatment weighting analysis of a multicenter cohort.

BACKGROUND: The association between blood culture status and mortality among sepsis patients remains controversial hence we conducted a tri-center retrospective cohort study to compare the early and late mortality of culture-negative versus culture-positive sepsis using the inverse probability of treatment weighting (IPTW) method. METHODS: Adult patients with suspected sepsis who completed the blood culture and procalcitonin tests in the emergency department or hospital floor were eligible for inclusion. Early mortality was defined as 30-day mortality, and late mortality was defined as 30- to 90-day mortality. IPTW was calculated from propensity score and was employed to create two equal-sized hypothetical cohorts with similar covariates for outcome comparison. RESULTS: A total of 1405 patients met the inclusion criteria, of which 216 (15.4%) yielded positive culture results and 46 (21.3%) died before hospital discharge. The propensity score model showed that diabetes mellitus, urinary tract infection, and hepatobiliary infection were independently associated with positive blood culture results. There was no significant difference in early mortality between patients with positive or negative blood culture results. However, culture-positive patients had increased late mortality as compared with culture-negative patients in the full cohort (IPTW-OR, 1.95, 95%CI: 1.14-3.32) and in patients with severe sepsis or septic shock (IPTW-OR, 1.92, 95%CI: 1.10-3.33). After excluding Staphylococcal bacteremia patients, late mortality difference became nonsignificant (IPTW-OR, 1.78, 95%CI: 0.87-3.62). CONCLUSIONS: Culture-positive sepsis patients had comparable early mortality but worse late mortality than culture-negative sepsis patients in this cohort. Persistent Staphylococcal bacteremia may have contributed to the increased late mortality.

Survival Impact and Clinical Predictors of Acute Gastrointestinal Bleeding in Patients With Bloodstream Infection.

PURPOSE: The impact of gastrointestinal bleeding (GIB) on outcomes of patients with bloodstream infection (BSI) has not been studied. We aim to evaluate the risk factors and survival impact of GIB on the outcome of BSI. MATERIALS AND METHODS: This study was conducted prospectively at National Taiwan University Hospital Yunlin Branch between January 1, 2015, and December 31, 2016. Patients aged ≥18 years for who BSI was confirmed by blood cultures were enrolled and followed for 90 days. Risk factors of GIB were identified by univariable and multivariable logistic regression models. The survival impact of GIB on BSI was evaluated with the Cox proportional hazards model with inverse probability of treatment weighting. RESULTS: Of the 1034 patients with BSI, 79 (7.64%) developed acute GIB. We identified 5 independent predictors of GIB. Patients with BSI complicated with GIB had an increased 90-day mortality compared to patients without GIB (hazard ratio 1.74, 95% confidence interval: 1.14, 2.65). CONCLUSIONS: Gastrointestinal bleeding had an adverse impact on the short-term survival in patients with BSI. The clinical predictors may help identify patients who may benefit from active prevention and treatment of GIB.

Manipulated Optical Absorption and Accompanied Photocurrent Using Magnetic Field in Charger Transfer Engineered C/ZnO Nanowires.

The rarely explored, spin-polarized band engineering, enables direct dynamic control of the magneto-optical absorption (MOA) and associated magneto-photocurrent (MPC) by a magnetic field, greatly enhancing the range of applicability of photosensitive semiconductor materials. It is demonstrated that large negative and positive MOA and MPC effects can be tuned alternately in amorphous carbon ( a-C )/ZnO nanowires by controlling the sp2/sp3 ratio of a-C . A sizeable enhancement of the MPC ratio (≈15%) appears at a relatively low magnetic field (≈0.2 T). Simulated two peaks spin-polarized density of states is applied to explain that the alternate sign switching of the MOA is mainly related to the charge transfer between ZnO and C. The results indicate that the enhanced magnetic field performance of ( a-C )/ZnO nanowires may have applications in renewable energy-related fields and tunable magneto-photonics.

Temporal trend and survival impact of infection source among patients with sepsis: a nationwide study.

BACKGROUND: To determine the temporal trends of incidence and outcome based on different sources of sepsis using a nationwide administrative database. METHODS: From 2002 to 2012, the entire Taiwan's health insurance claims data of emergency-treated and hospital-treated sepsis were analysed for incidence and mortality trends. The information about patients with sepsis and sources of sepsis was identified using a set of validated International Classification of Diseases, ninth revision, clinical modification (ICD-9-CM) codes. The 30-day all-cause mortality was verified by linked death certificate database. RESULTS: A total of 1 259 578 episodes of sepsis were identified during the 11-year study period. Lower respiratory tract infection is the most common source of sepsis in patients, with the highest mortality rate. The incidence of genitourinary tract infection has the fastest growing rate. The sepsis mortality was declining at different rates for each source of sepsis. Co-infections in patients with sepsis are associated with higher mortality rate. CONCLUSION: The temporal trends of sepsis incidence and mortality varied among different sources of sepsis, with lower respiratory tract being the highest burden among patients with sepsis. Furthermore, sources of sepsis and the presence of co-infection are independent predictors of mortality. Our results support source-specific preventive and treatment strategies for future sepsis management.

Incidence, trends, and outcomes of infection sites among hospitalizations of sepsis: A nationwide study.

PURPOSE: To determine the trends of infection sites and outcome of sepsis using a national population-based database. MATERIALS AND METHODS: Using the Nationwide Inpatient Sample database of the US, adult sepsis hospitalizations and infection sites were identified using a validated approach that selects admissions with explicit ICD-9-CM codes for sepsis and diagnosis/procedure codes for acute organ dysfunctions. The primary outcome was the trend of incidence and in-hospital mortality of specific infection sites in sepsis patients. The secondary outcome was the impact of specific infection sites on in-hospital mortality. RESULTS: During the 9-year period, we identified 7,860,687 admissions of adult sepsis. Genitourinary tract infection (36.7%), lower respiratory tract infection (36.6%), and systemic fungal infection (9.2%) were the leading three sites of infection in patients with sepsis. Intra-abdominal infection (30.7%), lower respiratory tract infection (27.7%), and biliary tract infection (25.5%) were associated with highest mortality rate. The incidences of all sites of infections were trending upward. Musculoskeletal infection (annual increase: 34.2%) and skin and skin structure infection (annual increase: 23.0%) had the steepest increase. Mortality from all sites of infection has decreased significantly (trend p<0.001). Skin and skin structure infection had the fastest declining rate (annual decrease: 5.5%) followed by primary bacteremia (annual decrease: 5.3%) and catheter related bloodstream infection (annual decrease: 4.8%). CONCLUSIONS: The anatomic site of infection does have a differential impact on the mortality of septic patients. Intra-abdominal infection, lower respiratory tract infection, and biliary tract infection are associated with higher mortality in septic patients.

Effect of Renin-Angiotensin-Aldosterone System Inhibitors on Short-Term Mortality After Sepsis: A Population-Based Cohort Study.

Antagonists of the renin-angiotensin-aldosterone system (RAAS), including ACEIs (angiotensin-converting enzyme inhibitors) and ARBs (angiotensin II receptor blockers), may prevent organ failure. We, therefore, investigated whether specific RAAS inhibitors are associated with reduced mortality in patients with sepsis.We conducted a population-based retrospective cohort study using multivariable propensity score-based regression to control for differences among patients using different RAAS inhibitors. A multivariable-adjusted Cox proportional-hazards regression model was used to determine the association between RAAS inhibitors and sepsis outcomes. To directly compare ACEI users, ARB users, and nonusers, a 3-way propensity score matching approach was performed. Results were pooled with previous evidence via a random-effects meta-analysis. A total of 52 727 patients were hospitalized with sepsis, of whom 7642 were prescribed an ACEI and 4237 were prescribed an ARB. Using propensity score-matched analyses, prior ACEI use was associated with decreased 30-day mortality (hazard ratio, 0.84 [95% CI, 0.75-0.94]) and 90-day mortality (hazard ratio, 0.83 [95% CI, 0.75-0.92]) compared with nonuse. Prior ARB use was associated with an improved 90-day survival (hazard ratio, 0.88 [95% CI, 0.83-0.94]). These results persisted in sensitivity analyses focusing on patients without cancer and patients with hypertension. By contrast, no beneficial effect was found for antecedent ß-blockers exposure (hazard ratio, 0.99 [95% CI, 0.94-1.05]). The pooled estimates obtained from the meta-analysis was 0.71 (95% CI, 0.58-0.87) for prior use of ACEI/ARB.The short-term mortality after sepsis was substantially lower among those who were already established on RAAS inhibitor treatment when sepsis occurred.

Accuracy of point-of-care ultrasound and radiology-performed ultrasound for intussusception: A systematic review and meta-analysis.

OBJECTIVE: It is unclear whether point-of-care ultrasound (POCUS) by emergency medicine physicians is as accurate as radiology-performed ultrasound (RADUS). We aim to summarize the diagnostic accuracy of ultrasonography for intussusception and to compare the performance between POCUS and RADUS. METHODS: Databases were searched from inception through February 2018 using pre-defined index terms. Peer-reviewed primary studies that investigated the diagnostic accuracy of ultrasound for intussusception in children were included. The study is reported using Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies (PRISMA-DTA). Meta-analysis of the diagnostic accuracy of ultrasound for intussusception was conducted using the random-effects bivariate model. Subgroup analysis (POCUS vs RADUS) was also performed. Meta-regression was utilized to determine if the diagnostic accuracy between POCUS and RADUS was significantly different. RESULTS: Thirty studies (n = 5249) were included in the meta-analysis. Ultrasonography for intussusception has a sensitivity: 0.98 (95% CI: 0.96-0.98), specificity: 0.98 (95% CI: 0.95-0.99), positive likelihood ratio: 43.8 (95% CI: 18.0-106.7) and negative likelihood ratio: 0.03 (95% CI: 0.02-0.04), with an area under ROC (AUROC) curve of 0.99 (95% CI: 0.98-1.00). Meta-regression suggested no significant difference in the diagnostic accuracy for intussusception between POCUS and RADUS (AUROC: 0.95 vs 1.00, p = 0.128). CONCLUSIONS: Current evidence suggested POCUS has a high diagnostic accuracy for intussusception not significantly different from that of RADUS.

Comparison of type B dissection by open, endovascular, and medical treatments.

OBJECTIVE: This study aimed to address the shortcomings of previous clinical trials that were inadequate to prove the superiority of thoracic endovascular aortic repair (TEVAR) in managing type B aortic dissection (TBAD) over open surgery (OS) or best medical treatment (BMT). The comparative effectiveness of these three treatments was analyzed using data of the National Inpatient Sample, a large U.S. database including patients from 4378 hospitals. METHODS: Adult patients diagnosed with a primary or secondary TBAD in the years 2005 to 2012 were included for analysis. Patients who had aortic aneurysm or received cardioplegia, valve repair, or operations on vessels of the heart were excluded. A three-category propensity score was created by using a multinomial logistic regression model, a three-way matching algorithm for 1:1:1 matching was applied, and a parallel outcome comparison between the three matched treatment groups was performed. RESULTS: Of a total of 54,971 patients included in the study, we matched 17,211 into three equal-size treatment groups (OS, 5755; TEVAR, 5695; BMT, 5761). No significant difference in the 22 baseline covariates was found in the matched cohort. We found TEVAR to have a much lower mortality rate than OS (odds ratio [OR], 0.60; 95% confidence interval [CI], 0.46-0.79) or BMT (OR, 0.62; 95% CI, 0.47-0.83). Mortality rates between OS and BMT were similar (OR, 0.97; 95% CI, 0.74-1.27). We also found TEVAR to have a lower complication rate, shorter hospitalization, and lower medical cost compared with OS. CONCLUSIONS: TEVAR is superior to BMT or OS for treatment of TBAD in terms of mortality, complications, and cost.